scholarly journals Classification of Guillain–Barré Syndrome Subtypes Using Sampling Techniques with Binary Approach

Symmetry ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 482
Author(s):  
Manuel Torres-Vásquez ◽  
Oscar Chávez-Bosquez ◽  
Betania Hernández-Ocaña ◽  
José Hernández-Torruco
Keyword(s):  
Predictive Models ◽  
Real Data ◽  
Machine Learning Algorithms ◽  
Guillain Barre Syndrome ◽  
Minority Class ◽  
Original Dataset ◽  
Appropriate Treatment ◽  
Binary Approach ◽  
Guillain Barré Syndrome ◽  
Guillain Barré

Guillain–Barré Syndrome (GBS) is an unusual disorder where the body’s immune system affects the peripheral nervous system. GBS has four main subtypes, whose treatments vary among them. Severe cases of GBS can be fatal. This work aimed to investigate whether balancing an original GBS dataset improves the predictive models created in a previous study. purpleBalancing a dataset is to pursue symmetry in the number of instances of each of the classes.The dataset includes 129 records of Mexican patients diagnosed with some subtype of GBS. We created 10 binary datasets from the original dataset. Then, we balanced these datasets using four different methods to undersample the majority class and one method to oversample the minority class. Finally, we used three classifiers with different approaches to creating predictive models. The results show that balancing the original dataset improves the previous predictive models. The goal of the predictive models is to identify the GBS subtypes applying Machine Learning algorithms. It is expected that specialists may use the model to have a complementary diagnostic using a reduced set of relevant features. Early identification of the subtype will allow starting with the appropriate treatment for patient recovery. This is a contribution to exploring the performance of balancing techniques with real data.

scholarly journals Reworsening of Recurrent Guillain-Barré Syndrome Triggered by COVID-19 Infection

2021 ◽  
Vol 15 (1) ◽  
pp. 48-51
Author(s):  
Gian Luca Vita ◽  
Carmen Terranova ◽  
Maria Sframeli ◽  
Antonio Toscano ◽  
Giuseppe Vita
Keyword(s):  
Viral Infection ◽  
Neurological Diseases ◽  
Intravenous Immunoglobulins ◽  
Guillain Barre Syndrome ◽  
Case Presentation ◽  
Appropriate Treatment ◽  
Immune Mediated ◽  
Guillain Barré Syndrome ◽  
Guillain Barré

Introduction: Guillain-Barré Syndrome (GBS) is an acute, immune-mediated, generalized polyradiculoneuropathy often triggered by a bacterial or viral infection, vaccination, or surgery. During the SARS-CoV-2 pandemic, some patients were reported with GBS associated COVID-19 infection. Case Presentation: We report, herein, a patient who had a recurrent GBS after forty years. Intravenous immunoglobulins (IVIg) induced improvement, but her condition worsened suddenly after twenty days, coinciding with a COVID-19 infection. A second IVIg cycle was administered, and she improved again. Conclusion: The take-home message is that in the current pandemic, any re-worsening or lack of improvement after appropriate treatment of GBS or possibly other autoimmune neurological diseases must be checked to determine if it is related to COVID-19 infection.

scholarly journals A Predictive Model for Guillain–Barré Syndrome Based on Ensemble Methods

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Juana Canul-Reich ◽  
José Hernández-Torruco ◽  
Oscar Chávez-Bosquez ◽  
Betania Hernández-Ocaña
Keyword(s):  
Predictive Model ◽  
Predictive Models ◽  
Ensemble Methods ◽  
Guillain Barre Syndrome ◽  
Computational Techniques ◽  
In Ovo ◽  
Adequate Treatment ◽  
Support Tool ◽  
Guillain Barré Syndrome ◽  
Guillain Barré

Nowadays, Machine Learning methods have proven to be highly effective on the identification of various types of diseases, in the form of predictive models. Guillain–Barré syndrome (GBS) is a potentially fatal autoimmune neurological disorder that has barely been studied with computational techniques and few predictive models have been proposed. In a previous study, single classifiers were successfully used to build a predictive model. We believe that a predictive model is imperative to carry out adequate treatment in patients promptly. We designed three classification experiments: (1) using all four GBS subtypes, (2) One versus All (OVA), and (3) One versus One (OVO). These experiments use a real-world dataset with 129 instances and 16 relevant features. Besides, we compare five state-of-the-art ensemble methods against 15 single classifiers with 30 independent runs. Standard performance measures were used to obtain the best classifier in each experiment. Derived from the experiments, we conclude that Random Forest showed the best results in four GBS subtypes classification, no ensemble method stood out over the rest in OVA classification, and single classifiers outperformed ensemble methods in most cases in OVO classification. This study presents a novel predictive model for classification of four subtypes of Guillain–Barré syndrome. Our model identifies the best method for each classification case. We expect that our model could assist specialized physicians as a support tool and also could serve as a basis to improved models in the future.

scholarly journals Major Surgery with Guillain-Barré Syndrome: A Case Report

2002 ◽  
Vol 30 (6) ◽  
pp. 601-604 ◽  
Author(s):  
M Koc ◽  
N Ozalp ◽  
B Zulfikaroglu
Keyword(s):  
Case Report ◽  
Surgical Stress ◽  
Guillain Barre Syndrome ◽  
Major Surgery ◽  
Progressive Muscle Weakness ◽  
Appropriate Treatment ◽  
Guillain Barré Syndrome ◽  
Triggering Factor ◽  
Guillain Barré ◽  
Cellular Immune

Guillain-Barré syndrome (GBS) is an acute demyelinating polyneuropathy characterized by progressive muscle weakness and areflexia. The pathogenesis of GBS is unknown, but it is generally believed to result from aberrant humoral and cellular immune responses against components of the peripheral nervous system. The overall prognosis of GBS is quite good with approximately 85% of survivors making a good functional recovery. When a diagnosis of GBS has been made, appropriate treatment should be started as early as possible. This may include supportive care in intensive care units, ventilatory assistance, monitoring of blood pressure, fluid status, cardiac rhythm, nutritional supports and medical therapy. Our patient reached maximum deficiency 3 weeks after the onset of GBS. Full recovery took 8 months. The occurrence of GBS after major surgery is rare. We believe that major surgical stress may be the potential triggering factor for the occurrence of GBS in this case report.

scholarly journals Guillain-Barre syndrome in 220 patients with COVID-19

2021 ◽  
Vol 57 (1) ◽  
Author(s):  
Josef Finsterer ◽  
Fulvio A. Scorza
Keyword(s):  
Early Diagnosis ◽  
Immune Reaction ◽  
Clinical Presentation ◽  
Guillain Barre Syndrome ◽  
Age Group ◽  
Appropriate Treatment ◽  
Guillain Barré Syndrome ◽  
Guillain Barré

AbstractThis review summarises and discusses recent findings concerning the pathophysiology, clinical presentation, diagnosis, treatment, and outcome of SARS-CoV-2-associated Guillain-Barre syndrome (SC2-GBS). By the end of December 2020, at least 220 patients with SC2-GBS have been published in 95 papers. SC2-GBS is most likely secondary due to an immune reaction against SARS-CoV-2 since the virus has not been found in the CSF of any SC2-GBS patient so far reported. SC2-GBS occurs in each age group and does not differ from non-SC2-GBS regarding clinical presentation and treatment, but the outcome of SC2-GBS is worse compared to non-CS2-GBS patients, and the prevalence/incidence of GBS most likely increased since the outbreak of the pandemic. Early diagnosis of SC2-GBS is warranted to apply appropriate treatment in due time and to improve the overall outcome from the infection.

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